Dental Office Management Case Study

How I helped an Indianapolis dental office through 100% turnover and go from their worst month ever to their best month ever in 2012.

When I worked as a business analyst at First Merchants I would often be doing staffing models during the day and working on web sites and IT work at night. After I was went full-time as a business consultant I offered staffing model services to one of my web clients. They trusted me because I had already got them to be #1 on Google for the term “Indianapolis Dentist” and their site was listed as one of the best dental websites.

Systems in Place

Systems in Place

The business owner wasn’t as interested in tracking what each individual staff member was doing as much as finding out what each staff member does, ensuring it’s documented, and making sure there were “systems in place”. At that point he had recently converted his practice management software from Practiceworks to Dentrix and two staff members had already quit. There was real fear of losing all “tribal knowledge” of how his business was ran.

Observations

One of the first things I do when I start a staffing model is to simply observe what is going on in the office. For the first two weeks I would ask questions, watch processes, and document as much as I could. If there was a name for a process I would use that – otherwise I would create a new name for it. I started identifying positions and roles (they can be different) and then placing the newly quantified tasks into ‘piles’ under each type.

Documentation

To document the process I setup the office with Google Apps and used the Google Sites portion of it to create an Intranet for the company. Each staff member was given their own company email address which they could use to login to the site as well as share calendars, documents, and email each other. Distribution groups were setup for different team members including the front office, clinical team, and the “everyone” group.

Employee Turnover

After a short while, a clear picture began to emerge. There weren’t just issues with cr0ss-training, there were issues with the staff themselves. It wasn’t long before there was more staff turnover. It was like they were “jumping ship”. The decision was made to get some new leadership into the organization so the long-time manager was fired in June. I became the interim manager and began to re-build the new staff.

Changes in Hiring Practices

One of the first things I focused on was “getting the right people on the bus”. We sought after and hired people who cared about people first and had a great personality. We had learned that those are two things that can’t be taught so those were the most important things we sought after. We didn’t settle for a person just because they filled the position and at some times were working with a crew of as small as 3 people while we continued to look.

Changes in Processes

Once we had the right people in place we began working on the proper processes. We started using checklists to ensure the critical morning and nightly procedures were completed. There were many times when they were not and the staff did not like using the checklists at first, but over time they learned to first appreciate them and then not need them as it became second-nature. This helped a brand new staff have consistency and learn faster.

Changes in Technology

While the old staff did not understand technology innately, the new staff embraced it. They began using email to communicate, began referencing the Intranet for critical information (the previous staff kept an old Rolodex on the front desk that contained all of the information they’d ever reference – this was typed up into one page on the Intranet affectionately titled, “Rolodex”). And a new wireless camera system was setup to take patient photos.

Changes in Marketing

We signed up for Demandforce and Angies List. We began using Google Adwords and revamped the website. We added more social proof, more testimonials, more web pages, and more blog posts. We added more social networks, posted more often, and were more engaged with our patients online. As a result, referrals from the Internet went up along with web site visitors. We used Google Analytics to track the progress.

The Result

By first focusing on the staff, then the process, then the technology, and finally the marketing – we had the right people who were given the right instructions for the best technology, which was supported by the best marketing techniques. The result was an initial boost of 116% the first month, followed by an average increase of 72% for the next five months compared to the five months prior. How can I help you get similar results?

10 Ways Businesses Can Use Analytics to Expand their Business

Businesses have more information stored on their customers and their business processes than ever before, which adds complexity in trying to collect, manage and interpret data into information that can help guide a business to success. Here are ten ways to use analytics to handle this complexity.

1. Get organized and get feedback.

The first step to any goal is to get organized. This could be an entire post in itself, but put simply, get rid of clutter in your computer and on your desk. Obstacles like bad file management (on your desk and in your computer) can eat up valuable brain cycles and time. Second, know what your resources are. This includes people, places, and things. Third, know where you want to end up. Begin with the end in mind. And four, which related so the first, have a place to store the plan once you create it. If you’ve done this before and have templates, use them. If you’re comfortable with a specific type of software that can help you, fine – use it. But don’t mistake learning a new process for moving forward on a project. Only tasks that move the project forward can be considered ‘working on the project’. If you have no idea what business analytic tools to use or where to start, go on to idea 2.

Web resources like Google Analytics can show you how far you’ve come in many customizable ways–number of visitors, sales goals, conversions, traffic sources, and top content. It can also tell you were your visitors are located, how long they stay on the site, which pages they enter and exit, and what day of the week they tend to visit. All of this information helps you know your visitors so you can improve their experience and improve your sales. Social places like Facebook, Twitter, & Youtube are also great places to get feedback from visitors on the products and services you offer. The more information you collect, the better your business will be. It’s true – content is king, but what you do with that content can make all the difference in the world.

2. Look for business analytics tools that are easy to use, flexible, and support a wide range of roles.

Usability and functionality—that is, business capabilities—stand out as manufacturing organizations’ most important considerations in selecting business analytics regardless of company size, individual role or functional area. These should be central focuses in evaluating tools. To be usable and functional, analytics systems must provide a range of options for how to include the information in presentations, which are increasing; participants indicated an interest most often in the standard charts, reports and tables. However, documents, visualizations such as gauges and sliders, text, Web pages and maps were also identified as important by one-third to one half of these companies. Determine which of these are important to your organization today and may be tomorrow.

The most important capability for an analytics system is to make it possible to search for specific existing answers. Because anomalies are common in business, individuals need to be able to drill down to find underlying causes. The second-most frequently chosen capability is exploring data underlying analytics, also deemed important or very important by nearly three-fourths. The participants rated similarly (22 percent to 28 percent deemed them very important) four other capabilities: to publish analytics and metrics; to explore data by working with maps, charts and tables; to set alerts and thresholds; and to collaborate in the review of analytics. The most important capability is being able to source data for the analytics. Without this capability it’s difficult to compile meaningful analytics. Equally important is the ability to take action based on the outcome of the analytics.

3. Prepare for growth by analyzing personnel.

Most people who have primary responsibility for designing and deploying analytics have experience with sophisticated tools. About half the time, analytics are designed and deployed by the business intelligence department, a data warehouse team, or by general IT resources. Line-of-business (LOB) analysts are involved the least, but in some cases collaborate. It helps when IT and the (LOB) work together on analytics. One example is to document tasks and documentation for each item in a ‘process map’ so that you are prepared for if you need to split a role, hire, or outsource some or all of those tasks due to volume or an influx of new tasks. The LOB analyst can then begin building a ‘staffing model’ which multiplies task volume by average task times to anticipate future personnel needs and analyze current business practices.

4. Assess the maturity of your business analytics.

While the Ventana Research Maturity Index placed 12 percent of respondents at the highest Innovative level in their use of analytics, 60 percent are in the bottom half of the maturity hierarchy. In people-related issues, the index identified lack of skilled resources and lack of executive support. Process-related issues included taking longer than a week to provide metrics from analytics, formally reviewing metrics no more often than quarterly or annually and low prioritization and lack of budget. In information-related issues that negatively impacted business analytics use, the research identified stale, outdated and inaccurate information as well as failing to prioritize basic informational needs. In the category of technology, the research found immature technology that is not working, unsophisticated technology known to be ineffective and a failure to prioritize forward-looking and predictive analytics. These shortcomings all impede a manufacturing organization’s effectiveness and performance and all need to be addressed.

5. Ensure business analytics are widely accessible.

In Ventana’s overall research on business analytics, only one-third of senior executives and one-fourth of vice presidents, directors and managers have analytics always available. While it is true that a large majority of executives have most of what they need, this is insufficient for optimally effective performance. Almost nine in 10 manufacturing organizations regard making it simpler to provide analytics and metrics to those who need them as important or very important. Also keep in mind that doing this from mobile devices such as smart phones and tablet computers will only increase in demand; already more than one-third of participants said this is important or very important.

6. Don’t let inferior data undermine use of business analytics and metrics.

Business analytics should be about determining what is happening and will happen to an organization. Most time is spent waiting for data, preparing data, and reviewing it for quality and consistency. Conversely, only a fraction of time is actually spent on true analysis processes such as assembling scenarios, searching for causes, and determining how changes will impact current business. If these preparation obstacles could be addressed, the amount of time people work with analytics could be reduced. Take steps to ensure your source data for analytics is both fresh and correct; if it isn’t, you risk undermining the use of metrics and KPIs as business improvement tools.

7. Replace spreadsheets as tools for business analytics.

Spreadsheets are well established as a tool for analysis in organizations of all kinds and sizes, but they are ineffective for repetitive analyses shared by more than a few people. Spreadsheets are the tools companies most commonly use to generate analytics, business intelligence technologies (for querying, reporting and performing analysis), and analytic warehouses and databases, but while they may be familiar, organizations using spreadsheets least have more accurate, timely data—and they deliver periodic reports about 40 percent sooner. Organizations should limit the use of spreadsheets as data stores and for repetitive analyses, particularly in cases where the results are reported to and used by more than a few people. Their failings, limitations and necessary work-arounds undermine the needs identified by participants to simplify analytics and metrics and ensure technology usability in the process of producing business analytics.

8. Understand the value of predictive and forward-looking analytics.

Predictive analytics can give a business glimpses of what may happen, the consequences of actions and scenarios for how to respond to change. Technology has advanced to a stage where it is feasible to provide them to a variety of users in manufacturing businesses. Yet the research shows predictive analytics are not yet high-priority analyst capabilities for the lines of business (LOB) nor are what-if and planning-based analytics; each is deemed very important by less than 30 in the LOBs. Exceptions were contact centers, in which predictive analytics ranked second-most important, and supply chains, where they are third-most important. Finance departments are the least likely to use predictive analytics even though they could be widely applicable within this function.

9. Resources must be adequate to enable investment in technology to make analytics easy to access and use.

Driving change and addressing barriers require understanding the benefits of investments. Demand that vendors show how their products deliver clear benefits such as these and address issues such as total cost of ownership and return on investment that can help lower the barriers in your organization. Consider cloud computing for deploying for business analytics. Slightly more than half of manufacturing organizations still prefer on-premises deployment for business analytics, but the research found a significant preference for software as a service, or cloud computing. Consider evaluating if your organization is looking to avoid the effort and expense of having in-house technology resources manage your business analytics.

10. Address barriers standing in the way of improving business analytics and performance.

The most significant barriers to making changes in analytics are fundamental:

  • Lack of resources
  • No budget
  • A business case that is not strong enough
  • Too low a priority assigned to the effort

To make matters worse, these barriers are interrelated. Failure to provide a compelling business case results in a project receiving a low priority and therefore not being allocated the resources or budget sufficient to implement the changes. And a failure to properly organize, begin with the end in mind, and forging on without gathering feedback, will all be obstacles in the way of having a successful project or business.

An Introduction to Staffing Models

Staffing Models is initially a two-step process of identifying the organizational mission, what metrics to track, and what processes there are. The next step is to find out how long it takes to do each task, how much volume they typically have, and then provide the tools to both track and report that information.

Utilization Reports

Utilization is a measure of how much work was accomplished with the hours spent. Tasks are determined to take an average amount of time, which is multiplied by task volume and divided by billed hours. The utilization report displays that information to evaluate and track the effectiveness of a department. Utilization is reflected in percent and optimal performance is considered to be between 90% and 100%.

Excess Capacity

Excess Capacity is the difference in time between what it should have taken to complete production and what we actually used to complete production. The white bar represents the time needed to complete the reported volume for each day and the red bar represents the excess capacity for that day in hours. Excess Capacity is a complementary metric to use in conjunction with Utilization to help management make staffing decisions in the future.

Dashboard Views

Executive dashboards provide an up-to-date snapshot of ongoing performance and trends. Dashboards should deliver clear, visual displays of a large set of data where performance is measured against expectations, goals, and deadlines. Production data is entered into the another tab within Excel for the appropriate date. The result is presented in final form on the “Report” tab, which is seen here to the left. This particular report uses micro-charts called sparklines and is designed to contain a rolling quarter year. This means the report will always have the previous two months data and the current months will be entered real-time at the bottom. Each rolling quarter is then archived for historical reporting at the end of each month.

Wedding Clocks

“Wedding Clocks” are a newly developed method for visually representing deadlines using special in-cell charts. In this example, the chart indicates the expectation for branches to have all batches transmitted by 6:30 PM, which is straight up and down on a clock. This chart points straight down (50% filled) at that goal and any result that varies from that (greater or lesser than 50% filled) is a reflection of meeting or exceeding that goal. Wedding Clocks are called this because Erich Stauffer noted that it is good luck to start a wedding at the bottom of the hour to catch the upswing of the second-hand. The range on both sides of 6:30 in this example is 3 hours (from 3:30 to 8:30).